code: def train_linear(
      num_workers=2, use_gpu=False, epochs=3, storage_path=None
  ):
      config = {
          "lr": 1e-2,
          "hidden_size": 1,
          "batch_size": 4,
          "epochs": epochs,
      }
      trainer = TorchTrainer(
          train_loop_per_worker=train_func,
          train_loop_config=config,
          scaling_config=ScalingConfig(
              num_workers=num_workers, use_gpu=use_gpu
          ),
          run_config=RunConfig(storage_path=storage_path),
      )
      result = trainer.fit()
  
      print(result.metrics)
      return result.metrics
  
file_path: ray/python/ray/train/examples/pytorch/torch_linear_example.py
imports: import argparse
  import os
  import tempfile
  import numpy
  import torch
  import torch.nn
  import ray.train
  from ray.train import Checkpoint, RunConfig, ScalingConfig
  from ray.train.torch import TorchTrainer
label_desc: Use image node_id 4 for calling a global function with example usage: train_linear(num_workers, use_gpu, epochs, storage_path) and returns: result